Article
Chemistry, Analytical
Jingqi Wang, Pingping Wang, Ruoyu Zhang, Wen Wu
Summary: This paper proposes a novel intercarrier interference (ICI)-free parameter estimation method for orthogonal frequency division multiplexing (OFDM) radar to address the performance degradation issue in range-velocity estimation in high mobility scenarios. By utilizing the scale discrete Fresnel transform (SDFnT), the OFDM radar signals are converted to the scale Fresnel domain, recovering the orthogonality of subcarriers with the optimal scale factor. The proposed method demonstrates low computational complexity and high feasibility for OFDM radar implementation due to the compatibility of SDFnT and discrete Fourier Transform (DFT). Simulation results show that the proposed SDFnT-based scheme effectively eliminates ICI effect and achieves accurate delay-Doppler estimation for OFDM radar systems in high velocity and low SNR scenarios with consistency and robustness.
Article
Engineering, Electrical & Electronic
J. Arun Kumar, S. Lenty Stuwart
Summary: A multi-stream cyclic interleaving architecture is proposed for an interleaved frequency division multiple access (IFDMA) system, allowing simultaneous transmission of multiple data streams and improving data rate. The proposal employs maximal ratio combining to maximize the signal-to-noise ratio.
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2023)
Article
Optics
Guozhou Jiang, Jintao Wu, Mengyan Li, Liu Yang
Summary: This paper introduces a method that utilizes deep neural network (DNN) to address the issue of intercarrier interference (ICI). Through studying and analyzing the intrinsic relationship between ICI damage mechanism and DNN, the performance of DNN-ICI decoder is compared with conventional algorithms through simulation experiments for optical SEFDM IM/DD communication systems. The results demonstrate that the DNN-ICI decoder, with a simple design, outperforms other schemes in terms of bit error rate (BER) under different bandwidth compression factors and is robust to fiber lengths. Therefore, the proposed DNN-ICI decoder shows great potential for application in SEFDM IM/DD optical systems.
OPTICAL ENGINEERING
(2022)
Article
Engineering, Marine
Haijun Wang, Weihua Jiang, Qing Hu, Jianjun Zhang, Yanqing Jia
Summary: Orthogonal frequency division multiplexing (OFDM) is the preferred scheme for high-speed communication in the field of underwater acoustic communication. This study proposes a time-varying CFO estimation method aided by the differential evolution (DE) algorithm to accurately estimate the CFO of an OFDM system. The simulation results show that the proposed method has a high estimation accuracy and outperforms other intelligent optimization algorithms. It also has good applicability to different modulation methods and reduces demodulation deterioration caused by noise.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Nan-Hung Cheng, Chien-Chung Chen, Yi-Fan Wang, Yung-Fang Chen
Summary: This paper proposes a CFO estimation algorithm with strong interference resistant capability for OFDMA systems. The algorithm includes two parts: the first part processes the received signals to solve the CFO estimation problem, and the second part uses an adaptive process to obtain the updated CFO estimation. Simulations show that the method is effective and performs close to the Cramer-Rao Bounds (CRB).
IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
N. Sathya Sheela, S. Lenty Stuwart
Summary: In this paper, a novel cyclic frequency division NOMA (CFD-NOMA) system is developed, integrating NOMA and IFDMA to enhance performance. The system utilizes the superposed multiuser principle for non-orthogonal resource allocation and employs successive interference cancellation to differentiate between strong users and cell edge users based on channel gain. The effective use of multipath channels in the CFD-NOMA system leads to improved cell edge user performance in terms of bit error rate (BER).
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Rongxin Zhang, Yiyin Wang, Xiaoli Ma
Summary: This letter studies the channel estimation problem in a cyclic-prefix OCDM system. The carrier frequency offset is compensated using the cyclic prefix, and a channel estimator based on superimposed pilot subchirps is proposed. The research results show that the proposed approach achieves superior performance compared to the state-of-the-art methods.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2022)
Article
Computer Science, Information Systems
Muhammad Sajid Sarwar, Soo Young Shin
Summary: This letter proposes the combination of spectrally efficient frequency division multiplexing (SEFDM) with orthogonal frequency division multiplexing (OFDM) using index modulation (IM). The article discusses the advantages of OFDM-SEM over classical OFDM-IM and SEFDM-IM in terms of bit error rate, as well as the impact of intercarrier interference and a potential solution through a pulse-shaping filter.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2023)
Article
Computer Science, Information Systems
Suvra Sekhar Das, Vivek Rangamgari, Shashank Tiwari, Subhas Chandra Mondal
Summary: This work introduces a time domain channel estimation method for OTFS to combat the impact of residual synchronization errors in high mobility scenarios. By analyzing the effects of residual synchronization errors, it is shown that OTFS exhibits better sparsity in time domain channel representation. In addition, utilizing low complexity MMSE equalization and SIC receiver can enhance system performance and mitigate against residual synchronization errors.
Article
Engineering, Electrical & Electronic
Minh Q. Nguyen, Reinhard Feger, Jonathan Bechter, Markus Pichler-Scheder, Martin H. Hahn, Andreas Stelzer
Summary: The article presents a method using RDMA and DDMA to achieve MIMO functionality for FMCW radars, with advantages including improved range and reduced image signals. Various modulation techniques are used to enable simultaneous transmission from multiple antennas and balance performance in angular resolution, range, and velocity measurements. The proposed system is verified using measurement data on a prototype with three TX and four receiving antennas.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2021)
Article
Engineering, Electrical & Electronic
Jie Ni, Jianping Zheng
Summary: This paper studies grant-free access technology for massive machine-type communication in the Internet of Things. The authors propose both coherent and non-coherent grant-free non-orthogonal multiple access (GF-NOMA) schemes, and present user-activity detection algorithms for both schemes. Computer simulations are conducted to demonstrate the effectiveness of the proposed algorithms.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Arthur S. de Sena, Pedro H. J. Nardelli, Daniel B. da Costa, Petar Popovski, Constantinos B. Papadias
Summary: This article presents the potential synergy between rate-splitting multiple access (RSMA) and intelligent reflecting surface (IRS). By flexibly managing interference, RSMA can improve the downlink performance of multiple-input multiple-output systems. IRS, on the other hand, can control the wireless environment through software configuration. The combination of RSMA and IRS can lead to significant improvements.
IEEE COMMUNICATIONS MAGAZINE
(2022)
Article
Engineering, Electrical & Electronic
Haibo Wang, Zaichen Zhang, Bingcheng Zhu, Jian Dang, Liang Wu, Ziyi Gong
Summary: This paper introduces the optical intelligent reflecting surface (OIRS) and its application in space division multiple access (SDMA) technology. Accurate SDMA is achieved by partitioning and controlling the OIRS, allowing a single OIRS to output multiple adjustable optical beams containing different information. Based on a mathematical model, closed-form expressions for the system's bit error rate (BER) and outage probability are derived. Numerical results confirm the accuracy of the derivations and reveal an error floor caused by multi-path interference among OIRS regions.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Shubham Anand, Subham Sabud, Amit Kumar Singh, Preetam Kumar
Summary: This paper proposes a novel discrete fractional Fourier transform (DFrFT) based OFDM-IM scheme to mitigate the inter-carrier interference (ICI) issue caused by carrier frequency offset (CFO) in index modulated OFDM systems. Theoretical calculations are conducted to determine the optimum DFrFT angle (cropt) for different CFO values. The proposed system achieves an 8 dB gain over conventional FFT-based OFDM-IM at BER = 10-3 in a high normalized CFO environment (e = 0.2). Simulation and analytical results demonstrate its robust and superior performance compared to other existing OFDM schemes, while maintaining the same complexity as the conventional FFT-based OFDM-IM system.
AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Yuting Zhan, Weile Zhang, Chen Wang, Zhijun Zhang
Summary: In this paper, a new multi-antenna transmission waveform is carefully designed to enable low-complexity anti-interference adaptive equalization. The proposed space-frequency adaptive equalization method makes use of mutual interferences among different antennas from the desired user rather than attempting to completely remove them. Two different ways to reduce computational complexity significantly are proposed based on subband-wise processing, showing significant gain over conventional anti-interference schemes in simulation results.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Marouan Othmani, Noureddine Boulejfen, Matias Turunen, Markus Allen, Fadhel M. Ghannouchi, Mikko Valkama
Summary: In this article, a new robust and highly efficient digital predistortion concept for the linearization of wideband RF power amplifiers is proposed. The concept combines a parallelized delta-sigma modulator and a forward model of the power amplifier, applying multi-rate techniques to handle high signal bandwidth. Three time-interleaved parallel DPD variants are introduced, offering improved linearization performance. Extensive real-world RF measurements validate the excellent transmit signal quality of the proposed approach.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Engineering, Electrical & Electronic
Vesa Lampu, Lauri Anttila, Matias Turunen, Marko Fleischer, Jan Hellmann, Mikko Valkama
Summary: This article models and develops effective cancellation schemes for passive intermodulation (PIM) distortion caused by external objects near the transmitter, known as air-induced PIM, in frequency-division duplex (FDD) multiple-input-multiple-output (MIMO) systems. The article presents a general model of the received air-induced PIM signal, and develops a cancellation scheme based on this model. To reduce complexity, an alternative cancellation scheme is proposed and validated through RF measurement-based experiments.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2023)
Article
Engineering, Electrical & Electronic
Jaakko Pihlajasalo, Dani Korpi, Mikko Honkala, Janne M. J. Huttunen, Taneli Riihonen, Jukka Talvitie, Alberto Brihuega, Mikko A. A. Uusitalo, Mikko Valkama
Summary: In this article, multiple machine learning receiver solutions are proposed for demodulating OFDM signals subject to high nonlinear distortion. Three deep learning-based convolutional neural network receivers are designed with layers in time and/or frequency domains to reliably demodulate and decode the transmitted bits despite high EVM in the signal. Training procedures are also described to generalize the learned layers over different nonlinear distortion and multipath channel characteristics. Numerical results show that the proposed ML receivers outperform classical LMMSE receivers and existing ML approaches, especially for high EVM. The hybrid nature of ML receivers with layers in both time and frequency improves terminal power-efficiency, radiated power, and network coverage. The proposed ML receivers can enhance maximum UL link distances by close to 100% compared to classical LMMSE receiver networks.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Telecommunications
Mateen Ashraf, Bo Tan, Dmitri Moltchanov, John S. S. Thompson, Mikko Valkama
Summary: This paper studies a dual functional radar communication (DFRC) system with multiple communication users (CUs) and a radar target. The goal is to optimize the beamforming vectors at the transmitter to enhance radar performance while satisfying the data rate requirements of CUs. Efficient algorithms based on convex optimization techniques are proposed to solve the formulated non-convex optimization problems. The results show that separate probing signals for radar detection are not needed in both clutter scenarios, reducing the complexity of the algorithm.
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING
(2023)
Article
Engineering, Electrical & Electronic
Alberto Brihuega, Lauri Anttila, Mikko Valkama
Summary: This article proposes a novel digital predistortion (DPD) solution for fully digital multiple-input-multiple-output (MIMO) transmitters (TXs). The proposed DPD operates at the stream or beam level, reducing the computational complexity of the overall system. It operates in the frequency domain, allowing flexible frequency-dependent linearization of transmit waveforms. The performance of the proposed solution is demonstrated and verified through experimental and simulation-based results.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2023)
Article
Engineering, Electrical & Electronic
Selahattin Gokceli, Taneli Riihonen, Toni Levanen, Mikko Valkama
Summary: This article proposes a novel machine learning-based solution, called PAPRer, for automatic and accurate tuning of the optimal PAPR target for frequency-selective PAPR reduction. The solution utilizes features related to the clipping noise filter and minimizes the defined loss function through supervised learning. Extensive numerical evaluations in 5G NR context demonstrate that PAPRer can accurately predict and tune the optimal PAPR target, offering a favorable performance-complexity tradeoff.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Yi Lu, Ossi Kaltiokallio, Mike Koivisto, Jukka Talvitie, Elena Simona Lohan, Henk Wymeersch, Mikko Valkama
Summary: In this article, an extended Kalman filtering (EKF)-based framework called MU-PoSAC is proposed to jointly estimate and track the locations and clock offsets of multiple users together with the unknown locations and orientation offsets of the anchors, using angle-of-arrival (AoA) and time-of-arrival (ToA) measurements. Numerical results show the feasibility of estimating and tracking the overall system state, the enhancement of estimation accuracy with a single reference anchor, and the better performance with more users. The framework also demonstrates robustness against intermittent Line-of-Sight (LoS) blockage in the considered industrial use case.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Arne Fischer-Buhner, Lauri Anttila, Manil Dev Gomony, Mikko Valkama
Summary: This letter presents a methodology for phase-normalization of the complex-valued I/Q inputs of a real-valued time delay neural network (RVTDNN). The normalization enables more efficient modeling of the nonlinear behavior of a radio frequency (RF) power amplifier (PA), complying with the physical characteristics of the distortions at RF. Digital predistortion (DPD) linearization experiments with a Doherty GaN PA at 3.5 GHz show significant improvement in output linearity compared to state-of-the-art neural network (NN) and polynomial-based DPD models, achieving linearization to below -50 dBc adjacent channel leakage ratio (ACLR) levels with feasible processing complexity.
IEEE MICROWAVE AND WIRELESS TECHNOLOGY LETTERS
(2023)
Proceedings Paper
Engineering, Electrical & Electronic
Ossi Kaltiokallio, Huseyin Yigitler, Jukka Talvitie, Mikko Valkama
Summary: Radio frequency sensor networks can be used for locating and tracking people without requiring them to carry any sensors or devices. This paper proposes a shift in focus from channel modeling to filter design, using random finite set theory and Bayesian filtering recursion to model detections, missed detections, false alarms, and unknown data association. Experimental results show that the proposed approach can reduce tracking error up to 48% compared to a benchmark solution.
2023 IEEE/ION POSITION, LOCATION AND NAVIGATION SYMPOSIUM, PLANS
(2023)
Proceedings Paper
Computer Science, Hardware & Architecture
Ali Goktas, Mateen Ashraf, Mikko Valkama, Bo Tan
Summary: This paper investigates the optimal joint radar and communications beamforming scheme with clutter to support low-space airborne vehicles, such as drones, in Non-Terrestrial Networks. The proposed scheme achieves the optimal signal-to-clutter-plus-noise ratio for sensing while maintaining the performance of communications. Numeric simulation results demonstrate that our approach maintains low complexity while guaranteeing the global optimum beamforming solution.
2023 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC
(2023)
Article
Computer Science, Theory & Methods
Guanxiong Shen, Junqing Zhang, Alan Marshall, Mikko Valkama, Joseph R. Cavallaro
Summary: This paper presents a neural network-based radio frequency fingerprint identification (RFFI) technique that can classify wireless devices by analyzing signal distortions caused by hardware impairments. To overcome the limitations of fixed-size input data and unsatisfactory performance in low signal-to-noise ratio (SNR) scenarios, four neural network models capable of processing signals of variable lengths are proposed, along with the use of data augmentation and multi-packet inference approaches to improve robustness and classification accuracy.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2023)
Article
Computer Science, Hardware & Architecture
Agnimesh Ghosh, Andrei Spelman, Tze Hin Cheung, Dhanashree Boopathy, Kari Stadius, Manil Dev Gomony, Mikko Valkama, Jussi Ryynanen, Marko Kosunen, Vishnu Unnikrishnan
Summary: This article presents an efficient implementation of a highly configurable DSP hardware generator for multiple transmitter architectures, supporting high sampling rates and a range of modulation schemes.
IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS
(2023)
Proceedings Paper
Automation & Control Systems
Moeinreza Golzadeh, Esa Tiirola, Lauri Anttila, Jukka Talvitie, Kari Hooli, Oskari Tervo, Ismael Peruga, Sami Hakola, Mikko Valkama
Summary: This paper investigates the potential of using existing 5G NR signals for network-side integrated sensing and communications (ISAC), and introduces a novel solution by combining SSB, DCI, and SIB1 symbols. Through realistic numerical evaluations, the proposed approach demonstrates significant improvements in radar peak sidelobe suppression and sensing resolution.
2023 IEEE 97TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2023-SPRING
(2023)
Proceedings Paper
Automation & Control Systems
Andrey Samuylov, Dmitri Molichanov, Juho Pirskanen, Jussi Numminen, Yevgeni Koucheryavy, Mikko Valkama
Summary: The recently standardized ETSI DECT-2020 NR technology is expected to enable operator-independent IoT services. Through system-level simulation, this paper evaluates coexistence solutions for DECT-2020 and classic DECT systems, showing that standard listen-before-talk access ensures excellent performance while last-minute scan leads to significant degradation in DECT-2020 performance.
2023 IEEE 97TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2023-SPRING
(2023)
